EEG
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Classification | EEG (5% labels) | Accuracy84.9 | 19 | |
| Classification | EEG (1% labels) | Accuracy77.95 | 19 | |
| Classification | EEG | Accuracy87.76 | 13 | |
| Temporal Attribution | EEG | I(100)83.99 | 13 | |
| Negative temporal attribution | EEG | Δŷc (2%)0.26 | 13 | |
| CASH | eeg (test) | Test Error0.0268 | 9 | |
| Classification | EEG | Accuracy85.56 | 8 | |
| EEG Classification | EEG Classification | Forward Latency (ms)0.03 | 8 | |
| Dynamical systems reconstruction | EEG 64d | Dstsp2.1 | 7 | |
| Classification | EEG (test) | Accuracy89 | 6 | |
| Classification | eeg UCI (test) | Accuracy78.5 | 6 | |
| Seizure classification | raw EEG | AUROC0.832 | 5 | |
| Multivariate Time Series Classification | EEG | Accuracy65.63 | 5 | |
| Addiction Detection | EEG dataset LOSO-CV (multi-seed) | Accuracy78.57 | 4 | |
| Zero-shot Class Generalization | EEG-CVPR40 zero-shot | KNN Accuracy99.7 | 3 | |
| Binary classification | EEG (test) | Binary Accuracy77.12 | 3 | |
| Frequency Change Detection | EEG | Detected Count46,604 | 2 | |
| Biosignal Inference | EEG 22-channel | Cycles629,400,000 | 1 | |
| Correlation Matrix Similarity Evaluation | EEG dataset | Metric- | 0 | |
| Few-shot Regression | EEG (out-of-range) | Metric- | 0 | |
| Few-shot Regression | EEG (in-range) | Metric- | 0 |
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